Zooplankton Bongo Net Data from the 2019 and 2020 Gulf of Alaska International Year of the Salmon Expeditions
Bibliographic record
Abstract
This record contains zooplankton occurrence data collected in the Gulf of Alaska (GoA) with a bongo net between February 19 - March 15, 2019, and March 14 – April 5, 2020, as part of the International Year of the Salmon High Seas Expedition. The bongo net (3 m length, 250 µm mesh, 50 cm diameter) was deployed at 58 stations, to a depth of 250 m and retrieved vertically at 1 m s-1. Volume of sea water filtered was determined using General Oceanics flowmeters and by multiplying effective distance travelled by the mouth area. After the bongo net deployment and recovery, the net was rinsed down into the cod end. Samples from one cod end were rinsed into a jar and preserved in 4 % formaldehyde for future taxonomic analysis. The other cod end was rinsed into a sieve and transferred below deck where it was subsequently size fractionated (250-500 µm, 500-1000 µm, 1000-2000 µm, 2000-4000 µm, and >4000 µm) onto pre-weighed filters. Individuals larger than 4000 µm were measured, identified to species level, and stored in individual Eppendorf tubes. Size fractionated zooplankton samples were stored on dry ice. This record contains the zooplankton occurrence data from both cod ends, identified to the lowest taxonomic rank possible.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.017 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".